John Steinert
Chief Marketing Officer, TechTarget

With greater accessibility to Big Data, modern marketers are exploring new ways to leverage data and scale targeting-related challenges at various stages of the buyer’s journey. Combining buyer’s profile with the intent data, marketers can build powerful automation channel and turn customer insights into a lead scoring machine. Powered by insight, Purchase Intent Insight by TechTarget is one such solution that amplifies intent behaviors from accounts and contacts active within your target segment to accelerate demand actions across marketing and sales operations. And then, TechTarget also partnered with the leading marketing and sales intelligence solution providers, DiscoverOrg and HG Data. To understand how marketers can master purchase intent in B2B marketing in 2018 and lift ABM performance with these partnerships, we spoke to TechTarget’s Chief Marketing Officer, John Steinert.

MTS: Tell us about your role at TechTarget and the team you handle?

John Steinert: I am the Chief Marketing Officer at TechTarget. My team and I are responsible for bringing the power of purchase intent-driven marketing and sales services to technology companies. Our 1,200+ customers look to us to learn how to leverage TechTarget’s unique purchase intent insight and advanced portfolio of marketing products and solutions to create more demand, achieve better conversion rates, accelerate ABM effectiveness and deliver a more substantial contribution to sales.

MTS: How do you build Purchase Intent for audiences across the buyer’s journey?

John: Real purchase intent insight is actually made, not scraped from general-purpose websites. It begins with relevant, useful content that provides critical value to professionals as they look to solve business challenges and make buying decisions. By observing and learning from their content consumption patterns as they happen, marketers can market and sellers can sell at the right time with greater relevance. Our ability to deliver real purchase intent starts with our extensive content footprint and the hyper-relevant audiences that we’ve built.

By creating abundant, high-quality editorial content across more than 140 highly targeted technology-specific websites and over 10,000 topics, TechTarget attracts and nurtures communities of technology buyers researching their companies’ information technology needs.

This content is designed to aid enterprise technology buyers in making real purchase decisions.

By understanding these buyers’ content consumption behavior, as well as the recency and velocity of activity within specific technology segments, we are able to deliver deep purchase intent insights on both an account and contact level to fuel efficient and effective marketing and sales activities. We provide these insights to customers within our Priority Engine platform, a SaaS-based solution that provides direct, real-time access to ranked accounts and named prospects actively researching purchases in specific technology categories.

MTS: How do the new improvements to the Priority Engine accelerate sales conversions?

John: Priority Engine’s new improvements accelerate sales conversions by providing more key information that B2B salespeople need to penetrate and drive engagement with accounts that are on a buyer’s journey. The platform provides direct access to real buyers at a critical point in time by ranking accounts based on purchase intent within their very specific technology segment. It helps the sales team identify and focus on the accounts that matter the most and helps them better identify and reach the entire Target Buying Team involved in the purchase, including active researchers and relevant stakeholders. With even better account coverage and our rich behavioral insight to personalize outreach, sales teams are able to convert prospects into customers at a higher rate.

MTS: Would you provide us a clear insight into how the latest partnerships with DiscoverOrg and HG Data offer deeper sales intelligence and better audience targeting?

John: With DiscoverOrg, we are able to expand our coverage of key stakeholders and buyers at accounts who are involved in the final purchase decision. We can now combine TechTarget’s insights into account purchase intent and named, active prospect activity with DiscoverOrg’s deep reach into an account’s extended buying team, all in one unified solution. This is something that is very powerful for our customers because it provides large productivity improvements.

In addition to deep reach into active accounts, TechTarget Priority Engine provides advanced views on their topical interests as well as information on which vendors they are considering. This is based on the full breadth of their editorial and promotional content consumption within specific technology segments. Our direct feed to HG Data’s rich technographic data ensures that marketing and sales teams’ have the best information available for knowing where a prospect is starting from and where they are heading.

These new partnerships bring improved audience targeting, deeper sales intelligence and new account insights to our customers to help them achieve vastly improved ROI for ABM, demand generation and sales enablement.

MTS: What are your views on GDPR and its impact on how ABM platforms utilize data? Would it derail the way modern CRMs intend to unify data for marketing and sales?

John: We welcome GDPR at TechTarget, as the relevant compliance efforts will initiate a more unified environment for marketers and a stronger relationship with their customers. GDPR is all about complying with an evolving sense of best practice, so marketers will only have a problem if the data they’re sourcing is of unknown and unmanaged provenance. It doesn’t really affect ABM platforms per se, it’s about the data — and the sourcing and management of it — that is being used. If you’re identifying a company through an IP lookup and using an email in your database that is permissible, for instance, there’s no issue. But if you’re obtaining email addresses from other sources that aren’t GDPR-compliant, then you could have a problem.

What GDPR means for marketers’ futures remains to be seen, but the bottom line is that marketers need to know where their data came from, the source needs to be compliant and they need to be able to manage the data competently. This won’t derail the way current processes are handled, it will just require more rigor and process capability. If companies already have mature data handling processes, they shouldn’t have any issue.

MTS: How would the landscape of predictive-driven content marketing and display advertising campaigns evolve over the next five years?

John: Predictive success is all about starting with the best possible data and then using it to the fullest. It all depends on having the right inputs and then generating the right outputs. The model itself achieves nothing for a company, it’s what they do with it. Predictive modeling has been around for a long time. What’s really new is a combination of the toolsets that make it easier to do and the concept of applying it to B2B marketing and sales.

The key determinants in how predictive will evolve over the next five years will be the quality of the data sources that are used to feed it, the evolution of the methods used to present and synchronize the advertising across touchpoints, and the behavior of the targeted audiences in response to it. If the data doesn’t improve, models will remain too weak to be worth their cost.  This will cause provider consolidation (which we are already seeing). If synchronization of delivery methods remains out of reach for many in B2B, the lift that we’ve proved can be achieved will remain out of reach to many.

And if the advertising itself fails to add recognized value — or at a minimum, support a business model which customers value — we will continue to see growth in blockers and blocking behaviors of all kinds. Nothing will kill advertising and content marketing like bad advertising techniques and bad content. Although modeling techniques will continue to drive down the cost of bad marketing by making it very clear what doesn’t work, predictive on its own will have little positive impact on specific campaign performance. In reality, this is what marketers are really pursuing — unless they use better data going into the model and take better actions when it comes out. In short, what we’ll see is an accelerated performance separation between the good marketers and everyone else.

MTS: Thanks for chatting with us, John.
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